The diversity of industry-university-government networks formed within regional clusters may dictate the degree of vigor of cutting-edge industries within a zone. After gaining a multidimensional grasp of the structural characteristics of the networks, we discuss their relationship with the location of concentrations of cutting-edge industries and with their growth. Specifically, we introduced certain network analysis methods and conducted quantitative analysis of health care-related industries in the Kinki (Osaka, Kyoto, Kobe) economic zone and the semiconductor industry in the northern Kyushu economic zone. As a result, we verified first that the networks in both regions and fields have the characteristics of 'small-world' networks; second, that within both networks there exist numerous modules in groupings of varying sizes, and that these have a loosely bound structure; third, that the groups of firms in same business fields within the health care-related industries in the Kinki region form tight horizontally linked modules, while among the system LSI and other semiconductor industries in northern Kyushu there is a mixture of modules formed by individual core manufacturers' vertically segmented keiretsu and horizontal collaboration, and differences in architecture between the two types were perceived; fourth, that there is a high degree of unity in the network within each discrete block-area economic zone; and fifth, that by means of microanalysis in which we observed the major nodes, we established that the core firms, research universities, trading companies, etc., in industrial fields act as connector hubs of the networks. In these two regions characterized by the remarkable concentration and growth of industries in cutting-edge fields, wide-area networks have been formed in a manner adapted for the rapid exchange and melding of information and knowledge, joint business activity, and industry-university collaboration. This indicates the possibility that excellent networks contribute to the nurturing of cutting-edge industries. In addition, in similar large-scale, cutting-edge industries, network structures differ according to the core industrial fields and regional characteristics. Policy efforts aimed at extending networks could be more effective if they were based on these structural characteristics.
[1]
C. Steinle,et al.
When do industries cluster? A proposal on how to assess an industry's propensity to concentrate at a single region or nation
,
2002
.
[2]
M E J Newman,et al.
Fast algorithm for detecting community structure in networks.
,
2003,
Physical review. E, Statistical, nonlinear, and soft matter physics.
[3]
Duncan J. Watts,et al.
Collective dynamics of ‘small-world’ networks
,
1998,
Nature.
[4]
George Kozmetsky,et al.
Creating the technopolis: High-technology development in Austin, Texas☆
,
1989
.
[5]
A. Rosenfeld Stuart,et al.
A Governor's guide to cluster-based economic development
,
2002
.
[6]
W. Powell,et al.
Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1
,
2005,
American Journal of Sociology.
[7]
Kenneth W. Koput,et al.
The Spatial Clustering of Science and Capital: Accounting for Biotech Firm-Venture Capital Relationships
,
2002
.
[8]
Walter W. Powell,et al.
Knowledge Networks as Channels and Conduits: The Effects of Spillovers in the Boston Biotechnology Community
,
2004,
Organ. Sci..
[9]
M. Porter.
Clusters and the new economics of competition.
,
1998,
Harvard business review.
[10]
Vincent Mangematin,et al.
THE DYNAMICS OF INNOVATION NETWORKS
,
2004
.